The Annals of Applied Statistics

Spurious predictions with random time series: The Lasso in the context of paleoclimatic reconstructions. Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?

Martin P. Tingley

Full-text: Open access

Article information

Source
Ann. Appl. Stat. Volume 5, Number 1 (2011), 83-87.

Dates
First available in Project Euclid: 21 March 2011

Permanent link to this document
http://projecteuclid.org/euclid.aoas/1300715180

Digital Object Identifier
doi:10.1214/10-AOAS398E

Mathematical Reviews number (MathSciNet)
MR2810387

Zentralblatt MATH identifier
05906796

Citation

Tingley, Martin P. Spurious predictions with random time series: The Lasso in the context of paleoclimatic reconstructions. Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?. Ann. Appl. Stat. 5 (2011), no. 1, 83--87. doi:10.1214/10-AOAS398E. http://projecteuclid.org/euclid.aoas/1300715180.


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References

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  • The Wall Street Journal (2010). Editorial: Climate of uncertainty, 02 September 2010. Available at http://online.wsj.com/article/SB10001424052748703467004575463433671739148.html.
  • Tingley, M. P. (2011). Supplement to “Spurious predictions with random time series: The Lasso in the context of paleoclimatic reconstructions. Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?” DOI: 10.1214/10-AOAS398ESUPP.
  • Tingley, M. P. and Huybers, P. (2010). A Bayesian algorithm for reconstructing climate anomalies in space and time. Part 1: Development and applications to paleoclimate reconstruction problems. Journal of Climate 23 2759–2781.
  • Tingley, M. P., Craigmile, P. F., Haran, M., Li, B., Mannshardt-Shamseldin, E. and Rajaratnam, B. (2010). Piecing together the past: Statistical insights into paleoclimatic reconstructions. Technical Report 2010–09. Dept. Statistics, Stanford Univ. Available at http://statistics.stanford.edu/~ckirby/reports/2010_2019/reports2010.html.

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